System and method for electronically identifying vehicle wheels on-the-fly during manufacture

Abstract

The method electronically identifies a vehicle wheel on-the-fly moving downstream from one processing location to another. The method includes the steps of locating a machine-readable identification mark applied to an exposed surface of the vehicle wheel as the vehicle wheel. The identification mark is electronically read on-the-fly.

Description

TECHNICAL FIELD AND BACKGROUND OF THE INVENTION [0001] The invention relates to a system and method for electronically identifying vehicle wheels on-the-fly during manufacture. The term “manufacture” is used broadly herein to include any sequential processing of the wheel prior to its actual mounting on a vehicle. In addition to vehicle wheels, the general concept of the present invention is applicable to any other item whose identification during or after manufacture is either necessary or desirable. [0002] The manufacturing of cast alloy wheels is generally an ordered process of sequential events. Some of these events are specific to an exact wheel model, while others are not. For example, machining is geometry specific, and if the wrong casting is loaded, a dangerous and expensive crash occurs. Heat-treating, on the other hand is non-specific and the wheel model is not so important. However, as heat-treating is approximately an one shift process, it is still useful to know what i...

AI Technical Summary

Benefits of technology

[0010] It is another object of the invention to provide a system and method for marking the vehicle wheel such that the wheel can be reliably machine-identified as it is conveyed into subsequent processes without stopping and rotating the wheel.

Problems solved by technology

For example, machining is geometry specific, and if the wrong casting is loaded, a dangerous and expensive crash occurs.

However, in higher volume automated operations, this is both expensive and less than 100% reliable.

While this is relatively straightforward for a human operator, it is a considerably more difficult task for machine vision, primarily because the snapshot is only a 2-D (two dimensional) image.

Often such systems are only effective when used in parallel with other inputs, and in some cases, series snapshots are required to eliminate the probability of misidentification.

The method is relatively expensive, cannot differentiate wheels that share much common geometry, and takes too much time for inline model identification without the massive parallelism that occurs in wheel machining.

While such lettering is readily seen in fluoroscopic images, and can be machine-recognized by optical character recognition (OCR), this technique is not a practical solution.

However, the low contrast surface makes this a more difficult task.

When low contrast bar codes are used, they are generally unreliable when read with conventional scanners.

While the system is relatively fast and reliable, it is considerably expensive and inefficient because the conveyed wheel must be stopped at the reader station and then rotated up to 360 degrees in order to locate and scan the code.

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